Process Optimization of Height Prediction of Water Flowing Fractured Zone Based on ANN
ZHAO Zhongming
LIU Yongliang
LI Yi
DONG Wei
SHI Tianwei
Abstract：In this paper, analysis was made on the factors affecting the height of water flowing fractured zone, which were then divided into the primary and secondary factors, and a system of factors affecting the height of water flowing fractured zone was constructed. BP neural network model was adopted and the thickness of coal seam, the lithological properties of roof rock, the dip angle of coal seam, the hardness of overlying rock, the inclined length of the working face, the advance speed and the bulking deformation of rock mass were chosen as the primary factors for predicting the height of the water flowing fractured zone, Under the determined geological condition, the secondary factors can be ignored in order to simplify the prediction model and accelerate the calculation. The prediction results showed that the simplified BP neural netwook model could meet the prediction accuracy of the height of water flowing fractured zone and this prediction method could provide a certain technical guidance for coal mining under water-bodies.
Keywords：ANN(artificial neural network)height of water flowing fractured zonepredictioncoal mining under water-bodies
Publication Date：2015-01-01
Online Publishing Date：2025-08-15(First online date of this platform, not the publication date of the document)
Pages：4( 47-49,53 )